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Please use this identifier to cite or link to this item: http://hdl.handle.net/11129/1604

Title: Bayesian Probability Estimation for Reasoning Process
Authors: Salehi, Sara
Keywords: Mathematics
Applied Mathematics and Computer Science
Probabilities - Bayesian statistical decision theory - Proposition (Logic) - Reasoning
Uncertainty, Bayesian Method, Subjective and Objective Probabilities, Bayesian Inference, Generalized Bayes' Theorem
Issue Date: May-2014
Publisher: Eastern Mediterranean University (EMU) - Doğu Akdeniz Üniversitesi (DAÜ)
Citation: Sara, Salehi. (2014). Bayesian Probability Estimation for Reasoning Process. Thesis (M.S.), Eastern Mediterranean University, Institute of Graduate Studies and Research, Dept. of Mathematics, Famagusta: North Cyprus.
Abstract: ABSTRACT: It is a comprehensible fact that people always desire to be able to remove or at least to decrease the level of uncertainty in real world application. In all the areas of science and technology, it is important to have an accurate measurement for evaluating the uncertainty. Increasing accuracy of measurement includes the identification, analysis and minimization of errors, compute and estimate the result of uncertainties. A probability is the branch of science studying the quantitative inferences of uncertainty. Probability is involved in various fields such as finance, meteorology, engineering, medicine, management etc. In this thesis, Bayesian probability estimation for reasoning process is analyzed. The conditional, joint, prior, and posterior probabilities are mentioned. The importance of the probability views based on the subjectivity and objectivity, and the properties of these two terms are considered. The Bayesian inference and the generalized Bayes’ theorem are discussed. Keywords: Uncertainty, Bayesian method, subjective and objective probabilities, Bayesian inference, generalized Bayes’ theorem. ………………………………………………………………………………………………………………………… ÖZ: Bilinen bir gerçektir ki insanlar farklı uygulamalarda belirsizlik derecesini yok etmeğe veya en azından küçültmeğe isteklidirler. Bilim ve teknolojinin tüm alanlarında belirsizliği değerlendirmek için hassas ölçüm gereklidir. Hassas ölçümü yükseltmek amacı ile belirsizliğin tanımlanması, tahlili, hatanın en az olması, sonuçların hesaplanması ve değerlendirilmesi gerekir. Olasılık bir bilim dalı olarak belirsizliğin nicel çıkarımlarını öğrenir. Olasılık finans, meteroloji, mühendislik, tıp ve başka alanlarda yer alır. Bu tezde Bayes olasılığı uslamlama işlemi için incelenir. Koşullu, bileşik, önsel, ve sonsal olasılıklardan bahsedilir. Öznellik ve nesnelliğe dayanan olasılık görünümlerinin önemi, ve bu iki kavramın özellikleri dikkate alınır. Bayes sonuç çıkarma ve genelleştirilmiş Bayes teoremi tartışılır. Anahtar Kelimeler: Belirsizlik, Bayes yöntemi, öznel ve nesnel olasılıklar, Bayes çıkarımı, genelleştirilmiş Bayes teoremi.
Description: Master of Science in Applied Mathematics and Computer Science. Thesis (M.S.)--Eastern Mediterranean University, Faculty of Arts and Sciences, Dept. of Mathematics, 2014. Supervisor: Prof. Dr. Rashad Aliyev.
URI: http://hdl.handle.net/11129/1604
Appears in Collections:Theses (Master's and Ph.D) – Mathematics

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